• Korean Institute of Interior Design Journal
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• no.28
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• pp.265-265
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• 2001

The perceptual presentation of interior design is to represent an interior space planned by a designer as if people see it in reality. The perceptual presentation methods that have developed are perspectives, full-scale models, small-scale models, photography of models, video taping of models, computer images, computer animation, and virtual reality. The purpose of this study is to investigate limits of those perceptual presentation methods according to their characteristics. The methods have characteristics that are either static or dynamic and either monoscopic or stereoscopic. In terms of representing interior spaces and perceiving interior spaces, the dynamic characteristic is more helpful than the static characteristic because the dynamic characteristic provides consecutively changing views of interior spaces when people walk around within the spaces. The stereoscopic characteristic is more helpful than the monoscopic characteristic because the stereoscopic characteristic provides the binocular depth perception. Full-scale models, small-scale models, virtual reality that have dynamic and stereoscopic characteristics, are most effective. The next effective methods are video taping of models and computer animation that have dynamic and monoscopic characteristics. The last effective methods are perspectives and photography of models that have static and monoscopic characteristics. But the most effective methods can not be said that those are perfect because each of them still has limits. Designers have to consider the limits of each perceptual presentation method to find a way that shows their designs most effectively. To develop the perceptual presentation methods of interior design, researchers should focus on the helpful characteristics that are dynamic and stereoscopic.

• Korean Institute of Interior Design Journal
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• no.29
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• pp.265-272
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• 2001

The perceptual presentation of interior design is to represent an interior space planned by a designer as if people see it in reality. The perceptual presentation methods that have developed are perspectives, full-scathe models, small-scale models, photography of models, video taping of models, computer images, computer animation, and virtual reality. The purpose of this study is to investigate limits of those perceptual presentation methods according to their characteristics. The methods have characteristics that are either static or dynamic and either monoscopic or stereoscopic. In terms of representing interior spaces and perceiving interior spaces, the dynamic characteristic is more helpful than the static characteristic because the dynamic characteristic provides consecutively changing views of interior spaces when people walk around within the spaces. The stereoscopic characteristic is more helpful than the monoscopic characteristic because the stereoscopic characteristic provides the binocular depth perception. Full-scale models, small-scale models, virtual reality that have dynamic and stereoscopic characteristics, are most effective. The next effective methods are video taping of models and computer animation that have dynamic and monoscopic characteristics. The last effective methods are perspectives and photography each of models that haute static and monoscopic characteristics. But the most effective methods can nut be said that those are perfect because each of them still has limits. Designers have to consider the limits of each perceptual presentation method to find a way that shows their designs most effectively. To develop the perceptual presentation methods of interior design, researchers should focus on the helpful characteristics that are dynamic and stereoscopic.

• Speech Sciences
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• v.9 no.1
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• pp.207-215
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• 2002

Perceptual evaluation of duration models of spoken Korean was carried out based on the Classification and Regression Tree (CART) model for text-to-speech conversion. A reference set of durations was produced by a commercial text-to-speech synthesis system for comparison. The duration model which was built in the previous research (Chung & Huckvale, 2001) was applied to a Korean language speech synthesis diphone database, 'Hanmal (HN 1.0)'. The synthetic speech produced by the CART duration model was preferred in the subjective preference test by a small margin and the synthetic speech from the commercial system was superior in the clarity test. In the course of preparing the experiment, a labeled database of spoken Korean with 670 sentences was constructed. As a result of the experiment, a trained duration model for speech synthesis was obtained. The 'Hanmal' diphone database for Korean speech synthesis was also developed as a by-product of the perceptual evaluation.

• Journal of the Korean housing association
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• v.10 no.4
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• pp.161-174
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• 1999

This study tried to search for solutions of present problems in architecture through interdisciplinary study which includes biology, literature, aesthetics, and psychology, and set up two models composed of the nature and the human perception which contemporary architecture has problems on. By nature-oriented approach through biology and romanticist literature, the five types of organic principles which could be obtained from structure and order in natural system and by human perception-oriented approach through aesthetic theory of Harold Osborne and perceptual and cognitive psychology the structure and order of perceptual arousal, perceptual balance, and perceptual order in human cognition based on perceptual appropriateness could be found. The unified and organic framework of architectural composition must be considered through a deductive and inductive study as this study was approached. The results of the present study can be applied to construct human-oriented design principles and factors in architectural space and form, and better environmental quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.570-595
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• 2017

Robust and perceptually-adaptive image watermarking algorithms have mainly targeted gray-scale images either at the modeling or embedding levels despite the widespread availability of color images. Only few of the existing algorithms are specifically designed for color images where color correlation and perception are constructively exploited. In this paper, a new perceptual and high-capacity color image watermarking solution is proposed based on the extension of Tsui et al. algorithm. The $CIEL^*a^*b^*$ space and the spatio-chromatic Fourier transform (SCFT) are combined along with a perceptual model to hide watermarks in color images where the embedding process reconciles between the conflicting requirements of digital watermarking. The perceptual model, based on an emerging color image model, exploits the non-uniform just-noticeable color difference (NUJNCD) thresholds of the $CIEL^*a^*b^*$ space. Also, spread-spectrum techniques and semi-random low-density parity check codes (SR-LDPC) are used to boost the watermark robustness and capacity. Unlike, existing color-based models, the data hiding capacity of our scheme relies on a game-theoretic model where upper bounds for watermark embedding are derived. Finally, the proposed watermarking solution outperforms existing color-based watermarking schemes in terms of robustness to standard image/color attacks, hiding capacity and imperceptibility.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.871-879
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• 2020

Perceptual Ad-Blocking is a new advertising blocking technique that detects online advertising by using an artificial intelligence-based advertising image classification model. A recent study has shown that these Perceptual Ad-Blocking models are vulnerable to adversarial attacks using adversarial examples to add noise to images that cause them to be misclassified. In this paper, we prove that existing perceptual Ad-Blocking technique has a weakness for several adversarial example and that Defense-GAN and MagNet who performed well for MNIST dataset and CIFAR-10 dataset are good to advertising dataset. Through this, using Defense-GAN and MagNet techniques, it presents a robust new advertising image classification model for adversarial attacks. According to the results of experiments using various existing adversarial attack techniques, the techniques proposed in this paper were able to secure the accuracy and performance through the robust image classification techniques, and furthermore, they were able to defend a certain level against white-box attacks by attackers who knew the details of defense techniques.

• Safety and Health at Work
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• v.12 no.4
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• pp.505-510
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• 2021

Background: Factors related to root causes can cause commonly occurring accidents such as falls, slips, and jammed injuries. An important means of reducing the frequency of occupational accidents in small- to medium-sized enterprises (SMSEs) of South Korea is to perform intensity analysis of the root cause factors for accident prevention in the cause and effect model like decision models, epidemiological models, system models, human factors models, LCU (life change unit) models, and the domino theory. Especially intensity analysis in a robot system and smart technology as Industry 4.0 is very important in order to minimize the occupational accidents and fatal accident because of the complexity of accident factors. Methods: We have developed the modern cause and effect model that includes factors of root cause through statistical testing to minimize commonly occurring accidents and fatal accidents in SMSEs of South Korea and systematically proposed educational policies for accident prevention. Results: As a result, the consciousness factors among factors of root cause such as unconsciousness, disregard, ignorance, recklessness, and misjudgment had strong relationships with occupational accidents in South Korean SMSEs. Conclusion: We conclude that the educational policies necessary for minimizing these consciousness factors include continuous training procedures followed by periodic hands-on experience, along with perceptual and cognitive education related to occupational health and safety.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4476-4491
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• 2021

Video service providers tend to face user network problems in the process of transmitting video streams. They strive to provide user with superior video quality in a limited bitrate environment. It is necessary to accurately determine the target bitrate range of the video under different quality requirements. Recently, several schemes have been proposed to meet this requirement. However, they do not take the impact of visual influence into account. In this paper, we propose a new multi-category model to accurately predict the target bitrate range with target visual quality by machine learning. Firstly, a dataset is constructed to generate multi-category models by machine learning. The quality score ladders and the corresponding bitrate-interval categories are defined in the dataset. Secondly, several types of spatial-temporal features related to VMAF evaluation metrics and visual factors are extracted and processed statistically for classification. Finally, bitrate prediction models trained on the dataset by RandomForest classifier can be used to accurately predict the target bitrate of the input videos with target video quality. The classification prediction accuracy of the model reaches 0.705 and the encoded video which is compressed by the bitrate predicted by the model can achieve the target perceptual quality.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.176-182
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• 2021

This paper evaluates and compares the performance of the Deep Nerual Network (DNN)-based speech enhancement models according to various loss functions. We used a complex network that can consider the phase information of speech as a baseline model. As the loss function, we consider two types of basic loss functions; the Mean Squared Error (MSE) and the Scale-Invariant Source-to-Noise Ratio (SI-SNR), and two types of perceptual-based loss functions, including the Perceptual Metric for Speech Quality Evaluation (PMSQE) and the Log Mel Spectra (LMS). The performance comparison was performed through objective evaluation and listening tests with outputs obtained using various combinations of the loss functions. Test results show that when a perceptual-based loss function was combined with MSE or SI-SNR, the overall performance is improved, and the perceptual-based loss functions, even exhibiting lower objective scores showed better performance in the listening test.

• Korea Trade Review
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• v.47 no.3
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• pp.37-55
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• 2022

This paper takes the factors influencing consumers' purchase of organic agricultural products before and after the COVID-19 epidemic as the starting point, decomposes Chinese consumers' purchase behavior of organic agricultural products into questionnaire surveys before and after the COVID-19 epidemic with the help of the theory of planned behavior, and builds structural equation regression models to compare and analyze them respectively. The study investigates whether this change has any impact on consumers' purchasing behavior of organic agricultural products, and proposes rationalized countermeasures from different perspectives based on the results of the study. To this end, this study collected 219 valid questionnaires by combing through domestic and international literature and referring to scholars' mature scales for measurement. The results showed that consumers' attitudes, subjective norms and perceptual behavioral control of organic agricultural products before and after the COVID-19 epidemic had a significant positive effect on consumers' willingness to purchase; however, it can be seen that the intervention of the COVID-19 epidemic event has significantly improved consumers' attitudes, subjective norms and perceptual behavioral control of organic agricultural products.